Tightening the bounds on feasible preemptions

• Authors: Harini Ramaprasad;Frank Mueller
• Venue: ACM Transactions on Embedded Computing Systems (TECS)
• Year: 2011

Data caches are an increasingly important architectural feature in most modern computer systems. They help bridge the gap between processor speeds and memory access times. One inherent difficulty of using data caches in a real-time system is the unpredictability of memory accesses, which makes it difficult to calculate worst-case execution times (WCETs) of real-time tasks. While cache analysis for single real-time tasks has been the focus of much research in the past, bounding the preemption delay in a multitask preemptive environment is a challenging problem, particularly for data caches. This article makes multiple contributions in the context of independent, periodic tasks with deadlines less than or equal to their periods executing on a single processor. 1) For every task, we derive data cache reference patterns for all scalar and nonscalar references. These patterns are used to derive an upper bound on the WCET of real-time tasks. 2) We show that, when considering cache preemption effects, the critical instant does not occur upon simultaneous release of all tasks. We provide results for task sets with phase differences to prove our claim. 3) We develop a method to calculate tight upper bounds on the maximum number of possible preemptions for each job of a task and, considering the worst-case placement of these preemption points, derive a much tighter bound on its WCET. We provide results using both static-and dynamic-priority schemes. Our results show significant improvements in the bounds derived. We achieve up to an order of magnitude improvement over two prior methods and up to half an order of magnitude over a third prior method for the number of preemptions, the WCET and the response time of a task. Consideration of the best-case and worst-case execution times of higher-priority jobs enables these improvements.